Month: April 2011

Congratulations to the seven students from Chennai who made it to Google Summer of Code. I am especially proud that they all participated in #32hourstartup and/or #in50hours product building events. Here is a list of the people selected.

#32hourstartup was the first weekend hackathon organized by students of SSN college and actively supported by other colleges. Yuvi from KCG Tech played a pivotal role in bringing this event along with Sharath and the team from SSN. They pulled off an amazing event and it was a privilege for some of us to be involved in that event. Nice to see that several students applied for GSOC and six of them were selected. To quote Yuvi:

People for whom 32HourStartup started the hackerspirit, eventually ending up in GSoC applications

That is really nice to know. You never think of these effects when you start these events.

#in50hours was another product building event organized as the launch of The Startup Centre in Chennai. There was considerable overlap between the participants of #32hourstartup and this event.

Some of these participants are regular contributors and participants in Chennai Geeks techmeets, Nerd Dinner casual meets and hang out in other startup communities like Chennai Open Coffee Club.

One thing is for sure. A tech/startup eco-system is emerging in Chennai and it is nice to be part of it all.

Meta:

Thanks to Yuvi for alerting me to this event (about 4 hours before the results were published) and pinging me immediately after to tell who was selected. Yuvi was selected last year also. He is the true inspiration behind all these participants.

Currently Mahout supports mainly four use cases: Recommendation mining takes users’ behavior and from that tries to find items users might like. Clustering takes e.g. text documents and groups them into groups of topically related documents. Classification learns from exisiting categorized documents what documents of a specific category look like and is able to assign unlabelled documents to the (hopefully) correct category. Frequent itemset mining takes a set of item groups (terms in a query session, shopping cart content) and identifies, which individual items usually appear together.

I feel like at least some of what gets communicated through Twitter reads to me like inner speech. The mechanism of Twitter seems to draw what might otherwise have stayed inner back into the uttered world. Maybe that’s not a bad thing. Maybe that’s part of the fascination–to feel like we’ve got a line into the running thoughts, observations, commentaries, and discoveries of an eclectic crowd, fragments of discourse that might otherwise never crystalize in language.

I was actually searching for the book titled “Drop that knowledge” when I discovered this post. A bit dated, perhaps, but resonate so well with it. To me , it is a like log of journey through the web of my own mind and some times a group mind.

They are published in the areas that include aviation, cancer, chemistry, computer science, food processing, food safety, genealogy, general medicine, geography, healthcare, manufacturing, mathematics, transportation, and weather. There are, in fact, hundreds of published ontologies.